Angelini, Enrico ; Campanini, Renato ; Iampieri, Emiro ; Lanconelli, Nico ; Masotti, Matteo ; Roffilli, Matteo
(2004)
Testing the performance of image
representations for mass classification in
digital mammograms.
[Preprint]
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Abstract
In this paper a two-class classification problem is faced. One class is constituted
by tumoral masses, breast tumors with size ranging from 3 mm to 30 mm. The
other class is constituted by non-masses. A Support Vector Machine (SVM) is used
as a classifier. Both, masses and non-masses, are extracted from the University
of South Florida (USF) mammographic image database and are presented to the
classifier as crops with pixel size 64 x 64. In order to find the optimal solution to
this problem, different featureless crops representations are evaluated. In particular,
a pixel-based representation, a Discrete Wavelet Transform (DWT) representation
and an Overcomplete Wavelet Transform (OWT) representation are tested.
Abstract
In this paper a two-class classification problem is faced. One class is constituted
by tumoral masses, breast tumors with size ranging from 3 mm to 30 mm. The
other class is constituted by non-masses. A Support Vector Machine (SVM) is used
as a classifier. Both, masses and non-masses, are extracted from the University
of South Florida (USF) mammographic image database and are presented to the
classifier as crops with pixel size 64 x 64. In order to find the optimal solution to
this problem, different featureless crops representations are evaluated. In particular,
a pixel-based representation, a Discrete Wavelet Transform (DWT) representation
and an Overcomplete Wavelet Transform (OWT) representation are tested.
Tipologia del documento
Preprint
Autori
Parole chiave
Wavelets, Image Processing, Support Vector Machine, Pattern Classification, Computer-Aided Detection in Mammography
Settori scientifico-disciplinari
DOI
Data di deposito
21 Ott 2004
Ultima modifica
16 Mag 2011 11:37
URI
Altri metadati
Tipologia del documento
Preprint
Autori
Parole chiave
Wavelets, Image Processing, Support Vector Machine, Pattern Classification, Computer-Aided Detection in Mammography
Settori scientifico-disciplinari
DOI
Data di deposito
21 Ott 2004
Ultima modifica
16 Mag 2011 11:37
URI
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Testing the performance of image
representations for mass classification in
digital mammograms. (deposited 21 Ott 2004)
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